937 resultados para Bromelia antiacantha extract


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Despite of improving levels of hygiene, the incidence of registered food borne disease has been at the same level for many years: there were 40 to 90 epidemics in which 1000-9000 persons contracted food poisoning through food or drinking water in Finland. Until the year 2004 salmonella and campylobacter were the most common bacterial causes of food borne diseases, but in years 2005-2006 Bacillus cereus was the most common. Similar developement has been published i.e. in Germany already in the 1990´s. One reason for this can be Bacillus cereus and its emetic toxin, cereulide. Bacillus cereus is a common environmental bacterium that contaminates raw materials of food. Otherwise than salmonella and campylobacter, Bacillus cereus is a heat resistant bacterium, capable of surviving most cooking procedures due to the production of highly thermo resistant spores. The food involved has usually been heat treated and surviving spores are the source of the food poisoning. The heat treatment induces germination of the spore and the vegetative cells then produce toxins. This doctoral thesis research focuses on developing methods for assessing and eliminating risks to food safety by cereulide producing Bacillus cereus. The biochemistry and physiology of cereulide production was investigated and the results were targeted to offer tools for minimizing toxin risk in food during the production. I developed methods for the extraction and quantitative analysis of cereulide directly from food. A prerequisite for that is knowledge of the chemical and physical properties of the toxin. Because cereulide is practically insoluble in water, I used organic solvents; methanol, ethanol and pentane for the extraction. For extraction of bakery products I used high temperature (100C) and pressure (103.4 bars). Alternaties for effective extraction is to flood the plain food with ethanol, followed by stationary equilibration at room temperature. I used this protocol for extracting cereulide from potato puree and penne. Using this extraction method it is also possible also extract cereulide from liquid food, like milk. These extraction methods are important improvement steps for studying of Bacillus cereus emetic food poisonings. Prior my work, cereulide extraction was done using water. As the result, the yield was poor and variable. To investigate suspected food poisonings, it is important to show actual toxicity of the incriminated food. Many toxins, but not cereulide, inactivate during food processing like heating. The next step is to identify toxin by chemical methods. I developed with my colleague Maria Andesson a rapid assay for the detection of cereulide toxicity, within 5 to 15 minutes. By applying this test it is possible to rapidly detect which food was causing the food poisoning. The chemical identification of cereulide was achieved using mass spectrometry. I used cereulide specific molecular ions, m/z (+/-0.3) 1153.8 (M+H+), 1171.0 (M+NH4+), 1176.0 (M+Na+) and 1191.7 (M+K+) for reliable identification. I investigated foods to find out their amenability to accumulate cereulide. Cereulide was formed high amounts (0.3 to 5.5 microg/g wet wt) when of cereulide producing B. cereus strains were present in beans, rice, rice-pastry and meat-pastry, if stored at non refrigerated temperatures (21-23C). Rice and meat pastries are frequently consumed under conditions where no cooled storage is available e.g. picnics and outdoor events. Bacillus cereus is a ubiquitous spore former and is therefore difficult to eliminate from foods. It is therefore important to know which conditions will affect the formation of cereulide in foods. My research showed that the cereulide content was strongly (10 to 1000 fold differences in toxin content) affected by the growth environment of the bacterium. Storage of foods under nitrogen atmosphere (> 99.5 %) prevented the production of cereulide. But when also carbon dioxide was present, minimizing the oxygen contant (< 1%) did not protect the food from formation of cereulide in preliminary experiments. Also food supplements affected cereulide production at least in the laboratory. Adding free amino acids, leucine and valine, stimulated cereulide production 10 to 20 fold. In peptide bonded form these amino acids are natural constituents in all proteins. Interestingly, adding peptide bonded leucine and valine had no significant effect on cereulide production. Free amino acids leucine and valine are approved food supplements and widely used as flawour modifiers in food technology. My research showed that these food supplements may increase food poisoning risk even though they are not toxic themselves.

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The purpose of this work was to identify some of the genes of the catabolic route of L-rhamnose in the yeast Pichia stipitis. There are at least two distinctly different pathways for L-rhamnose catabolism. The one described in bacteria has phosphorylated intermediates and the enzymes and the genes of this route have been described. The pathway described in yeast does not have phosphorylated intermediates. The intermediates and the enzymes of this pathway are known but none of the genes have been identified. The work was started by purifying the L-rhamnose dehydrogenase, which oxidates L-rhamnose to rhamnonic acid-gamma-lactone. NAD is used as a cofactor in this reaction. A DEAE ion exchange column was used for purification. The active fraction was further purified using a non-denaturing PAGE and the active protein identified by zymogram staining. In the last step the protein was separated in a SDS-PAGE, the protein band trypsinated and analysed by MALDI-TOF MS. This resulted in the identification of the corresponding gene, RHA1, which was then, after a codon change, expressed in Saccharomyces cerevisiae. Also C- or N-terminal histidine tags were added but as the activity of the enzyme was lost or strongly reduced these were not used. The kinetic properties of the protein were analysed in the cell extract. Substrate specifity was tested with different sugars; L-rhamnose, L-lyxose and L-mannose were oxidated by the enzyme. Vmax values were 180 nkat/mg, 160 nkat/mg and 72 nkat/mg, respectively. The highest affinity was towards L-rhamnose, the Km value being 0.9 mM. Lower affinities were obtained with L-lyxose, Km 4.3 mM, and L-mannose Km 25 mM. Northern analysis was done to study the transcription of RHA1 with different carbon sources. Transcription was observed only on L-rhamnose suggesting that RHA1 expression is L-rhamnose induced. A RHA1 deletion cassette for P. stipitis was constructed but the cassette had integrated randomly and not targeted to delete the RHA1 gene. Enzyme assays for L-lactaldehyde dehydrogenase were done similarly to L-rhamnose dehydrogenase assays. NAD is used as a cofactor also in this reaction where L-lactaldehyde is oxidised to L-lactate. The observed enzyme activities were very low and the activity was lost during the purification procedures.

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Soil testing is the most widely used tool to predict the need for fertiliser phosphorus (P) application to crops. This study examined factors affecting critical soil P concentrations and confidence intervals for wheat and barley grown in Australian soils by interrogating validated data from 1777 wheat and 150 barley field treatment series now held in the BFDC National Database. To narrow confidence intervals associated with estimated critical P concentrations, filters for yield, crop stress, or low pH were applied. Once treatment series with low yield (<1 t/ha), severe crop stress, or pHCaCl2 <4.3 were screened out, critical concentrations were relatively insensitive to wheat yield (>1 t/ha). There was a clear increase in critical P concentration from early trials when full tillage was common compared with those conducted in 1995–2011, which corresponds to a period of rapid shift towards adoption of minimum tillage. For wheat, critical Colwell-P concentrations associated with 90 or 95% of maximum yield varied among Australian Soil Classification (ASC) Orders and Sub-orders: Calcarosol, Chromosol, Kandosol, Sodosol, Tenosol and Vertosol. Soil type, based on ASC Orders and Sub-orders, produced critical Colwell-P concentrations at 90% of maximum relative yield from 15 mg/kg (Grey Vertosol) to 47 mg/kg (Supracalcic Calcarosols), with other soils having values in the range 19–27 mg/kg. Distinctive differences in critical P concentrations were evident among Sub-orders of Calcarosols, Chromosols, Sodosols, Tenosols, and Vertosols, possibly due to differences in soil properties related to P sorption. However, insufficient data were available to develop a relationship between P buffering index (PBI) and critical P concentration. In general, there was no evidence that critical concentrations for barley would be different from those for wheat on the same soils. Significant knowledge gaps to fill to improve the relevance and reliability of soil P testing for winter cereals were: lack of data for oats; the paucity of treatment series reflecting current cropping practices, especially minimum tillage; and inadequate metadata on soil texture, pH, growing season rainfall, gravel content, and PBI. The critical concentrations determined illustrate the importance of recent experimental data and of soil type, but also provide examples of interrogation pathways into the BFDC National Database to extract locally relevant critical P concentrations for guiding P fertiliser decision-making in wheat and barley.

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1. Saline extract of sheep pancreas acetone-dried powder was shown to catalyse acyl ester hydrolysis of spinach leaf galactosyl diglycerides and also galactosylglucosyl diglyceride of Lactobacillus casei. 2. Sodium deoxycholate stimulated the enzyme activity. Ca2+ had no effect on the hydrolysis of monogalactosyl diglyceride, but it enhanced that of digalactosyl diglyceride. When added together, there was considerably less activity with both the substrates. 3. Optimal hydrolysis was observed at pH7.2. 4. The initial point of hydrolysis was at position-1, leading to the formation of monogalactosyl monoglyceride and digalactosyl monoglyceride. Further hydrolysis to the corresponding galactosylglycerols and later to galactose and glycerol was also observed, indicating the presence of a- and b-galactosidases in the enzyme preparation. 5. Formation of monogalactosyl diglyceride from digalactosyl diglyceride by the action of a-galactosidase was noted. 6. Monogalactosyl diglyceride was also hydrolysed by b-galactosidase to a limited extent, giving rise to diacylglycerol and galactose. 7. Attempts at purification of monogalactosyl diglyceride acyl hydrolase by using protamine sulphate treatment, Sephadex G-100 filtration and DEAE-cellulose chromatography gave a partially purified enzyme which showed 9- and 81-fold higher specific activity towards monogalactosyl diglyceride and digalactosyl diglyceride respectively. This still showed acyl ester hydrolysis activity towards methyl oleate, phosphatidylcholine and triacylglycerol. 8. When sheep, rat and guinea-pig tissues were compared, guinea-pig tissues showed the highest activity towards both monogalactosyl diglyceride and digalactosyl diglyceride. In all the species pancreas showed higher activity than intestine.

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The results of research into the water relations and irrigation requirements of lychee are collated and reviewed. The stages of plant development are summarised, with an emphasis on factors influencing the flowering process. This is followed by reviews of plant water relations, water requirements, water productivity and, finally, irrigation systems. The lychee tree is native to the rainforests of southern China and northern Vietnam, and the main centres of production remain close to this area. In contrast, much of the research on the water relations of this crop has been conducted in South Africa, Australia and Israel where the tree is relatively new. Vegetative growth occurs in a series of flushes. Terminal inflorescences are borne on current shoot growth under cool (<15 °C), dry conditions. Trees generally do not produce fruit in the tropics at altitudes below 300 m. Poor and erratic flowering results in low and irregular fruit yields. Drought can enhance flowering in locations with dry winters. Roots can extract water from depths greater than 2 m. Diurnal trends in stomatal conductance closely match those of leaf water status. Both variables mirror changes in the saturation deficit of the air. Very little research on crop water requirements has been reported. Crop responses to irrigation are complex. In areas with low rainfall after harvest, a moderate water deficit before floral initiation can increase flowering and yield. In contrast, fruit set and yield can be reduced by a severe water deficit after flowering, and the risk of fruit splitting increased. Water productivity has not been quantified. Supplementary irrigation in South-east Asia is limited by topography and competition for water from the summer rice crop, but irrigation is practised in Israel, South Africa, Australia and some other places. Research is needed to determine the benefits of irrigation in different growing areas. Copyright © Cambridge University Press 2013.

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Fluorinated surfactant-based aqueous film-forming foams (AFFFs) are made up of per- and polyfluorinated alkyl substances (PFAS) and are used to extinguish fires involving highly flammable liquids. The use of perfluorooctanesulfonic acid (PFOS) and other perfluoroalkyl acids (PFAAs) in some AFFF formulations has been linked to substantial environmental contamination. Recent studies have identified a large number of novel and infrequently reported fluorinated surfactants in different AFFF formulations. In this study, a strategy based on a case-control approach using quadrupole time-of-flight tandem mass spectrometry (QTOF-MS/MS) and advanced statistical methods has been used to extract and identify known and unknown PFAS in human serum associated with AFFF-exposed firefighters. Two target sulfonic acids [PFOS and perfluorohexanesulfonic acid (PFHxS)], three non-target acids [perfluoropentanesulfonic acid (PFPeS), perfluoroheptanesulfonic acid (PFHpS), and perfluorononanesulfonic acid (PFNS)], and four unknown sulfonic acids (Cl-PFOS, ketone-PFOS, ether-PFHxS, and Cl-PFHxS) were exclusively or significantly more frequently detected at higher levels in firefighters compared to controls. The application of this strategy has allowed for identification of previously unreported fluorinated chemicals in a timely and cost-efficient way.

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It has been demonstrated that most cells of the body respond to osmotic pressure in a systematic manner. The disruption of the collagen network in the early stages of osteoarthritis causes an increase in water content of cartilage which leads to a reduction of pericellular osmolality in chondrocytes distributed within the extracellular environment. It is therefore arguable that an insight into the mechanical properties of chondrocytes under varying osmotic pressure would provide a better understanding of chondrocyte mechanotransduction and potentially contribute to knowledge on cartilage degeneration. In this present study, the chondrocyte cells were exposed to solutions with different osmolality. Changes in their dimensions and mechanical properties were measured over time. Atomic Force Microscopy (AFM) was used to apply load at various strain-rates and the force-time curves were logged. The thin-layer elastic model was used to extract the elastic stiffness of chondrocytes at different strain-rates and at different solution osmolality. In addition, the porohyperelastic (PHE) model was used to investigate the strain-rate dependent responses under the loading and osmotic pressure conditions. The results revealed that the hypo-osmotic external environment increased chondrocyte dimensions and reduced Young’s modulus of the cells at all strain-rates tested. In contrast, the hyper-osmotic external environment reduced dimensions and increased Young’s modulus. Moreover, by using the PHE model coupled with inverse FEA simulation, we established that the hydraulic permeability of chondrocytes increased with decreasing extracellular osmolality which is consistent with previous work in the literature. This could be due to a higher intracellular fluid volume fraction with lower osmolality.

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Comprehensive two-dimensional gas chromatography (GC×GC) offers enhanced separation efficiency, reliability in qualitative and quantitative analysis, capability to detect low quantities, and information on the whole sample and its components. These features are essential in the analysis of complex samples, in which the number of compounds may be large or the analytes of interest are present at trace level. This study involved the development of instrumentation, data analysis programs and methodologies for GC×GC and their application in studies on qualitative and quantitative aspects of GC×GC analysis. Environmental samples were used as model samples. Instrumental development comprised the construction of three versions of a semi-rotating cryogenic modulator in which modulation was based on two-step cryogenic trapping with continuously flowing carbon dioxide as coolant. Two-step trapping was achieved by rotating the nozzle spraying the carbon dioxide with a motor. The fastest rotation and highest modulation frequency were achieved with a permanent magnetic motor, and modulation was most accurate when the motor was controlled with a microcontroller containing a quartz crystal. Heated wire resistors were unnecessary for the desorption step when liquid carbon dioxide was used as coolant. With use of the modulators developed in this study, the narrowest peaks were 75 ms at base. Three data analysis programs were developed allowing basic, comparison and identification operations. Basic operations enabled the visualisation of two-dimensional plots and the determination of retention times, peak heights and volumes. The overlaying feature in the comparison program allowed easy comparison of 2D plots. An automated identification procedure based on mass spectra and retention parameters allowed the qualitative analysis of data obtained by GC×GC and time-of-flight mass spectrometry. In the methodological development, sample preparation (extraction and clean-up) and GC×GC methods were developed for the analysis of atmospheric aerosol and sediment samples. Dynamic sonication assisted extraction was well suited for atmospheric aerosols collected on a filter. A clean-up procedure utilising normal phase liquid chromatography with ultra violet detection worked well in the removal of aliphatic hydrocarbons from a sediment extract. GC×GC with flame ionisation detection or quadrupole mass spectrometry provided good reliability in the qualitative analysis of target analytes. However, GC×GC with time-of-flight mass spectrometry was needed in the analysis of unknowns. The automated identification procedure that was developed was efficient in the analysis of large data files, but manual search and analyst knowledge are invaluable as well. Quantitative analysis was examined in terms of calibration procedures and the effect of matrix compounds on GC×GC separation. In addition to calibration in GC×GC with summed peak areas or peak volumes, simplified area calibration based on normal GC signal can be used to quantify compounds in samples analysed by GC×GC so long as certain qualitative and quantitative prerequisites are met. In a study of the effect of matrix compounds on GC×GC separation, it was shown that quality of the separation of PAHs is not significantly disturbed by the amount of matrix and quantitativeness suffers only slightly in the presence of matrix and when the amount of target compounds is low. The benefits of GC×GC in the analysis of complex samples easily overcome some minor drawbacks of the technique. The developed instrumentation and methodologies performed well for environmental samples, but they could also be applied for other complex samples.

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The antibacterial activity and total phenolic (TP) content of Agaricus bisporus stipes were assessed using solvent and water extracts to determine its bioactivity. Extraction methods included accelerated solvent extraction (ASE) and hot water followed by membrane concentration. Water extract from ASE had the highest TP of 1.08 gallic acid equivalents (GAE)/g dry weight (DW) followed by ethanol at 0.61 mg GAE/g DW and 0.11 mg GAE/g DW for acetone. Acetone extracts inhibited Escherichia coli and Staphylococcus aureus at less than 50%; ethanol inhibited E. coli at 61.9% and S. aureus at 56.6%; and ASE water inhibited E. coli at 78.6% and S. aureus at 65.4%. The TP content of membrane concentrated extract of mushroom was 17 mg GAE in 100 mL. Membrane concentrated water extracts had a higher percentage inhibition on S. aureus than E. coli. Overall, the results were promising for further application of mushroom stipe extracts as a functional food additive. Practical Applications Mushrooms are known for their health benefits and have been identified as a good source of nutrients. The highly perishable nature of mushrooms warrants further processing and preservation to minimize losses along the supply chain. This study explores the possibility of adding value to mushroom stipes, a by-product of the fresh mushroom industry. The extracts assessed indicate the antibacterial activity and phenolic content, and the potential of using these extracts as functional ingredients in the food industry. This study provides valuable information to the scientific community and to the industries developing novel ingredients to meet the market demand for natural food additives.

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User generated information such as product reviews have been booming due to the advent of web 2.0. In particular, rich information associated with reviewed products has been buried in such big data. In order to facilitate identifying useful information from product (e.g., cameras) reviews, opinion mining has been proposed and widely used in recent years. In detail, as the most critical step of opinion mining, feature extraction aims to extract significant product features from review texts. However, most existing approaches only find individual features rather than identifying the hierarchical relationships between the product features. In this paper, we propose an approach which finds both features and feature relationships, structured as a feature hierarchy which is referred to as feature taxonomy in the remainder of the paper. Specifically, by making use of frequent patterns and association rules, we construct the feature taxonomy to profile the product at multiple levels instead of single level, which provides more detailed information about the product. The experiment which has been conducted based upon some real world review datasets shows that our proposed method is capable of identifying product features and relations effectively.

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Abstract: Although mainly grown for its sweet flavoured fruit, papaya (Carica papaya) has also been used for pharmacological purposes for many years. The reasons for use are varied with one of the best known being its anti-fungal action. Benzyl isothiocyanate (BITC) is the constituent most often implicated in this activity. Isothiocyanates are formed when the enzyme myrosinase catalyses the hydrolysis of the non-bioactive glucosinolates. This occurs when cellular contents come into contact through chewing, cutting or during extraction processes in the laboratory. While this is common in Brassica vegetables, the glucosinolate-myrosinase system is rare in fruit, papaya being a notable exception. It contains benzyl glucosinolate (BG), the glucosinolate precursor of BITC, in significant quantities. Parameters that determine the amount of BITC formed are duration of hydrolysis, presence/absence of nitrile-specifier proteins and BG content of different cultivars and tissues. We experimented with differing BITC extraction solvents, with the intention of developing a low cost, natural anti-fungal extract based on under-utilised papaya tissues. The findings suggest that papaya seeds, particularly from quarter-ripe fruit, have the potential to produce the highest levels of BITC necessary. Furthermore, they compare well with the nitrile-specifier protein-containing garden cress seeds (Lepidium sativum). To utilise the papaya seeds as a BITC source, an organic solvent such as ethanol is required to extract the largely water-insoluble BITC from the hydrolysed papaya seed mixture.

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The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.

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A central tenet in the theory of reliability modelling is the quantification of the probability of asset failure. In general, reliability depends on asset age and the maintenance policy applied. Usually, failure and maintenance times are the primary inputs to reliability models. However, for many organisations, different aspects of these data are often recorded in different databases (e.g. work order notifications, event logs, condition monitoring data, and process control data). These recorded data cannot be interpreted individually, since they typically do not have all the information necessary to ascertain failure and preventive maintenance times. This paper presents a methodology for the extraction of failure and preventive maintenance times using commonly-available, real-world data sources. A text-mining approach is employed to extract keywords indicative of the source of the maintenance event. Using these keywords, a Naïve Bayes classifier is then applied to attribute each machine stoppage to one of two classes: failure or preventive. The accuracy of the algorithm is assessed and the classified failure time data are then presented. The applicability of the methodology is demonstrated on a maintenance data set from an Australian electricity company.

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The antibacterial activity and total phenolic (TP) content of Agaricus bisporus stipes were assessed using solvent and water extracts to determine its bioactivity. Extraction methods included accelerated solvent extraction (ASE) and hot water followed by membrane concentration. Water extract from ASE had the highest TP of 1.08 gallic acid equivalents (GAE)/g dry weight (DW) followed by ethanol at 0.61 mg GAE/g DW and 0.11 mg GAE/g DW for acetone. Acetone extracts inhibited Escherichia coli and Staphylococcus aureus at less than 50%; ethanol inhibited E. coli at 61.9% and S. aureus at 56.6%; and ASE water inhibited E. coli at 78.6% and S. aureus at 65.4%. The TP content of membrane concentrated extract of mushroom was 17 mg GAE in 100 mL. Membrane concentrated water extracts had a higher percentage inhibition on S. aureus than E. coli. Overall, the results were promising for further application of mushroom stipe extracts as a functional food additive. Practical Applications Mushrooms are known for their health benefits and have been identified as a good source of nutrients. The highly perishable nature of mushrooms warrants further processing and preservation to minimize losses along the supply chain. This study explores the possibility of adding value to mushroom stipes, a by-product of the fresh mushroom industry. The extracts assessed indicate the antibacterial activity and phenolic content, and the potential of using these extracts as functional ingredients in the food industry. This study provides valuable information to the scientific community and to the industries developing novel ingredients to meet the market demand for natural food additives.

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Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.